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An HMM-Based Subband Processing Approach to Speaker Identification

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Audio- and Video-Based Biometric Person Authentication (AVBPA 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2091))

Abstract

This paper contributes to the growing literature confirming the effectiveness of subband processing for speaker recognition. Specifically, we investigate speaker identification from noisy test speech modelled using linear prediction and hidden Markov models (HMMs). After filtering the wideband signal into subbands, the output time trajectory of each is represented by 12 pseudo-cepstral coefficients which are used to train and test individual HMMs. During recognition, the HMM outputs are combined to produce an overall score for each test utterance. We find that, for particular numbers of filters, subband processing outperforms traditional wideband techniques.

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Author information

Authors and Affiliations

  1. Image, Speech and Intelligent Systems Research Group Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK

    J. E. Higgins & R. I. Damper

Authors
  1. J. E. Higgins
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  2. R. I. Damper
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Editor information

Editors and Affiliations

  1. School of Information Science, Computer and Electrical Engineering, Halmstad University, P.O. Box 823, S-301 18, Halmstad, Sweden

    Josef Bigun  & Fabrizio Smeraldi  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Higgins, J.E., Damper, R.I. (2001). An HMM-Based Subband Processing Approach to Speaker Identification. In: Bigun, J., Smeraldi, F. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2001. Lecture Notes in Computer Science, vol 2091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45344-X_24

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  • DOI: https://doi.org/10.1007/3-540-45344-X_24

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42216-7

  • Online ISBN: 978-3-540-45344-4

  • eBook Packages: Springer Book Archive

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